Agent skill

Scientific Illustration Guide

by wentorai in wentorai/research-plugins

Create graphical abstracts, schematic diagrams, and scientific illustrations

MITAuto-check passedDevelopment

Install Scientific Illustration Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill scientific-illustration-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins scientific-illustration-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tools/diagram/scientific-illustration-guide .claude/skills/scientific-illustration-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scientific-illustration-guide
GitHub stars
298
Used in
1 other repo
Token cost
~2k tokens
SKILL.md length
240 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Create graphical abstracts, schematic diagrams, and scientific illustrations

  • Works in 5 steps: Never use red and green together to… → Use both color and shape/pattern to… → Ensure sufficient contrast (WCAG AA:… → …
  • Tasks that involve Diagrams
  • SKILL.md covers Graphical Abstract Design, Schematic Diagrams, Vector Graphics with Drawio and Color and Accessibility, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Scientific Illustration Guide is an agent skill from wentorai/research-plugins. Create graphical abstracts, schematic diagrams, and scientific illustrations

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Diagrams. It works with draw.io. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Diagrams

Example prompts

  • “/scientific-illustration-guide”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Never use red and green together to encode different categories
  2. Use both color and shape/pattern to distinguish elements
  3. Ensure sufficient contrast (WCAG AA: 4.5:1 ratio for text)
  4. Test your diagram in grayscale to verify it remains interpretable
  5. Label elements directly rather than relying solely on a color legend

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and xml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scientific Illustration Guide loads about 2k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 240 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~27
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 240 words, ~2,020 tokens.

Download SKILL.mdSave it as .claude/skills/scientific-illustration-guide/SKILL.md (or your agent's skills folder).
name
scientific-illustration-guide
description
Create graphical abstracts, schematic diagrams, and scientific illustrations

Scientific Illustration Guide

A skill for creating clear, professional scientific illustrations including graphical abstracts, schematic diagrams, workflow visualizations, and architecture diagrams. Covers both programmatic and design tool approaches.

Graphical Abstract Design

Composition Principles
Layout Guidelines for Graphical Abstracts:
  - Dimensions: typically 500x300px to 1200x800px (check journal spec)
  - Flow direction: left-to-right or top-to-bottom
  - Maximum 5-7 visual elements
  - Use arrows to show process flow
  - Include 1-2 key data points or results
  - Minimal text (30-50 words maximum)
  - Consistent color scheme (3-4 colors)

Structure:
  [Input/Problem] --> [Method/Process] --> [Output/Finding]
Programmatic Diagrams with Python
python
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from matplotlib.patches import FancyBboxPatch, FancyArrowPatch

def create_workflow_diagram(steps: list[dict], output: str = 'workflow.pdf'):
    """
    Create a horizontal workflow diagram.

    Args:
        steps: List of dicts with 'label', 'color', and optional 'sublabel'
        output: Output file path
    """
    fig, ax = plt.subplots(figsize=(12, 3))
    n = len(steps)
    box_width = 0.12
    gap = (1 - n * box_width) / (n + 1)

    for i, step in enumerate(steps):
        x = gap + i * (box_width + gap)
        y = 0.3

        # Draw box
        box = FancyBboxPatch(
            (x, y), box_width, 0.4,
            boxstyle="round,pad=0.01",
            facecolor=step.get('color', '#3B82F6'),
            edgecolor='#1E293B',
            linewidth=1.5,
            alpha=0.9
        )
        ax.add_patch(box)

        # Add label
        ax.text(x + box_width/2, y + 0.2, step['label'],
                ha='center', va='center', fontsize=9,
                fontweight='bold', color='white')

        if 'sublabel' in step:
            ax.text(x + box_width/2, y - 0.08, step['sublabel'],
                    ha='center', va='center', fontsize=7, color='#475569')

        # Draw arrow to next step
        if i < n - 1:
            ax.annotate('', xy=(x + box_width + gap*0.2, 0.5),
                        xytext=(x + box_width + gap*0.8, 0.5),
                        arrowprops=dict(arrowstyle='->', color='#64748B',
                                       lw=1.5))

    ax.set_xlim(0, 1)
    ax.set_ylim(0, 1)
    ax.axis('off')
    fig.savefig(output, dpi=300, bbox_inches='tight',
                facecolor='white', edgecolor='none')
    plt.close()
    return output

# Example: research pipeline
steps = [
    {'label': 'Data\nCollection', 'color': '#3B82F6', 'sublabel': 'N=1,200'},
    {'label': 'Preprocessing', 'color': '#6366F1', 'sublabel': 'QC + Filtering'},
    {'label': 'Analysis', 'color': '#8B5CF6', 'sublabel': 'ML Pipeline'},
    {'label': 'Validation', 'color': '#A855F7', 'sublabel': 'Cross-validation'},
    {'label': 'Results', 'color': '#EC4899', 'sublabel': 'AUC = 0.92'}
]
create_workflow_diagram(steps, 'research_pipeline.pdf')

Schematic Diagrams

System Architecture Diagrams
python
import matplotlib.pyplot as plt
from matplotlib.patches import FancyBboxPatch, FancyArrowPatch

def create_architecture_diagram(components: list[dict],
                                  connections: list[tuple],
                                  output: str = 'architecture.pdf'):
    """
    Create a system architecture diagram.

    Args:
        components: List of {'name', 'x', 'y', 'width', 'height', 'color', 'type'}
        connections: List of (source_name, target_name, label) tuples
    """
    fig, ax = plt.subplots(figsize=(10, 7))

    # Draw components
    comp_positions = {}
    for comp in components:
        x, y = comp['x'], comp['y']
        w, h = comp.get('width', 1.5), comp.get('height', 0.8)
        color = comp.get('color', '#3B82F6')

        if comp.get('type') == 'database':
            # Cylinder shape for databases
            ellipse_h = 0.15
            ax.add_patch(patches.Rectangle((x, y), w, h-ellipse_h,
                         facecolor=color, edgecolor='#1E293B', linewidth=1.2))
            ax.add_patch(patches.Ellipse((x+w/2, y+h-ellipse_h), w, ellipse_h*2,
                         facecolor=color, edgecolor='#1E293B', linewidth=1.2))
            ax.add_patch(patches.Ellipse((x+w/2, y), w, ellipse_h*2,
                         facecolor=color, edgecolor='#1E293B', linewidth=1.2))
        else:
            box = FancyBboxPatch((x, y), w, h,
                                  boxstyle="round,pad=0.05",
                                  facecolor=color, edgecolor='#1E293B',
                                  linewidth=1.2, alpha=0.9)
            ax.add_patch(box)

        ax.text(x + w/2, y + h/2, comp['name'],
                ha='center', va='center', fontsize=10,
                fontweight='bold', color='white')

        comp_positions[comp['name']] = (x + w/2, y + h/2, w, h)

    # Draw connections
    for src, tgt, label in connections:
        sx, sy, sw, sh = comp_positions[src]
        tx, ty, tw, th = comp_positions[tgt]

        ax.annotate('', xy=(tx, ty + th/2 if sy > ty else ty - th/2),
                    xytext=(sx, sy - sh/2 if sy > ty else sy + sh/2),
                    arrowprops=dict(arrowstyle='->', color='#64748B',
                                   lw=1.5, connectionstyle='arc3,rad=0.1'))

        mid_x = (sx + tx) / 2
        mid_y = (sy + ty) / 2
        if label:
            ax.text(mid_x + 0.1, mid_y, label, fontsize=7, color='#475569')

    ax.set_xlim(-0.5, 10)
    ax.set_ylim(-0.5, 8)
    ax.set_aspect('equal')
    ax.axis('off')
    fig.savefig(output, dpi=300, bbox_inches='tight',
                facecolor='white')
    plt.close()

Vector Graphics with Drawio

For complex diagrams, use draw.io (diagrams.net) which exports to SVG, PDF, and PNG:

xml
<!-- Example draw.io XML structure -->
<mxGraphModel>
  <root>
    <mxCell id="0"/>
    <mxCell id="1" parent="0"/>
    <mxCell id="2" value="Data Source" style="rounded=1;fillColor=#3B82F6;
            fontColor=#FFFFFF;strokeColor=#1E40AF;" vertex="1" parent="1">
      <mxGeometry x="80" y="80" width="120" height="60" as="geometry"/>
    </mxCell>
  </root>
</mxGraphModel>
Diagram TypeBest ToolOutput FormatLearning Curve
Flowchartsdraw.io / MermaidSVG, PDFLow
Molecular structuresChemDraw / RDKitSVG, PNGMedium
Biological pathwaysBioRender / KEGGPNG, SVGLow
Network graphsCytoscape / NetworkXSVG, PDFMedium
3D protein structuresPyMOL / ChimeraXPNG, TIFFHigh
Circuit diagramsKiCad / CircuiTikZPDF, SVGMedium
Math diagramsTikZ/PGFPDFHigh
UML diagramsPlantUML / MermaidSVG, PNGLow

Color and Accessibility

Use colorblind-safe palettes consistently. The key rules:

  1. Never use red and green together to encode different categories
  2. Use both color and shape/pattern to distinguish elements
  3. Ensure sufficient contrast (WCAG AA: 4.5:1 ratio for text)
  4. Test your diagram in grayscale to verify it remains interpretable
  5. Label elements directly rather than relying solely on a color legend

Export and Journal Compliance

  • Export vector formats (SVG, PDF, EPS) for line art and diagrams
  • Minimum 300 DPI for raster elements within diagrams
  • Embed fonts or convert text to paths in final SVG/PDF
  • Check journal-specific requirements for graphical abstract dimensions and file size
  • Name files following journal convention (e.g., "Figure_1.pdf", "graphical_abstract.tiff")

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/tools/diagram/scientific-illustration-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Scientific Illustration Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Scientific Illustration Guide compared with similar skills
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Scientific Illustration Guide this skillwentorai/research-plugins2981 repos~2kAutomated safety check: PassMIT
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Draw.io Diagram ReconstructionHKUSTDial/Supervisor-Skills8.8k—~5.4kAutomated safety check: PassMIT
Scibox Diagramjihe520/sci-box2491 repos~983Automated safety check: NotesNone
Drawio Diagram BuilderWill-hxw/drawio-diagram-builder413—~5.9kAutomated safety check: PassMIT

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Works with

Categories

Questions about Scientific Illustration Guide

What does Scientific Illustration Guide do?

Create graphical abstracts, schematic diagrams, and scientific illustrations. Scientific Illustration Guide is an agent skill from wentorai/research-plugins.

When should I use Scientific Illustration Guide?

Scientific Illustration Guide fits situations like: tasks that involve Diagrams.

How do I install Scientific Illustration Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill scientific-illustration-guide -a claude-code`. Or copy the skill folder (skills/tools/diagram/scientific-illustration-guide in wentorai/research-plugins) into .claude/skills/scientific-illustration-guide in your project. Claude Code loads it when a task matches its description.

How do I install Scientific Illustration Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill scientific-illustration-guide -a codex`. Or copy the skill folder (skills/tools/diagram/scientific-illustration-guide in wentorai/research-plugins) into .agents/skills/scientific-illustration-guide in your project. Codex loads it when a task matches its description.

Can I use Scientific Illustration Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill scientific-illustration-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scientific-illustration-guide, .gemini/skills/scientific-illustration-guide, .github/skills/scientific-illustration-guide and .opencode/skills/scientific-illustration-guide in your project.

What does Scientific Illustration Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Scientific Illustration Guide is instructions for the agent only. Our summary lists: Python 3.

Does Scientific Illustration Guide access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Scientific Illustration Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Scientific Illustration Guide use?

Scientific Illustration Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scientific Illustration Guide use?

About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scientific Illustration Guide?

Skills that share tags, products or a category with Scientific Illustration Guide: Diagram Design (cathrynlavery/diagram-design, 49k stars), Draw.io Diagram Studio (Agents365-ai/drawio-skill, 10k stars), Draw.io Diagram Reconstruction (HKUSTDial/Supervisor-Skills, 8.8k stars) and Scibox Diagram (jihe520/sci-box, 249 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scientific Illustration Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.